Abstract
In this paper, we present a study on the discrimination capabilities of colour, texture and shape MPEG-7 [1] visual descriptors, within the context of video sequences. The target is to facilitate the recognition of certain visual cues which would then allow the classification of natural disaster-related concepts. Low-level visual features are extracted using the MPEG-7 “eXperimentation Module” (XM) [2]. The extraction times associated to the levels of detail of the descriptors are measured. The pattern sets obtained as combination of significant levels of detail of different descriptors are the input to a Support Vector Machine (SVM), resulting on the classification accuracies. Preliminary results indicate that this approach could be useful for the implementation of real-time spatial regions classifiers.
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Molina, J., Spyrou, E., Sofou, N., Martínez, J.M. (2007). On the Selection of MPEG-7 Visual Descriptors and Their Level of Detail for Nature Disaster Video Sequences Classification. In: Falcidieno, B., Spagnuolo, M., Avrithis, Y., Kompatsiaris, I., Buitelaar, P. (eds) Semantic Multimedia. SAMT 2007. Lecture Notes in Computer Science, vol 4816. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77051-0_6
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DOI: https://doi.org/10.1007/978-3-540-77051-0_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-77033-6
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